Early detection of breast cancer is widely believed to increase the likelihood of successful treatment of the disease. Although X-ray mammography is an important tool in breast cancer detection, its limitations are well recognized. Microwave imaging using ultra wideband (UWB) radar techniques is one promising alternative for breast cancer detection, Preliminary studies suggest that UWB microwave radar has the potential to detect and localize very small tumors (less than 0.5 cm) in the breast, The proposed research is an investigation of additional signal processing techniques for improving medical imaging. These techniques will be developed and applied in the context of microwave imaging for breast cancer detection. The specific aims of the proposal are 1) to identify a model of the clutter due to normal breast tissue; 2) to verify the clutter model; 3) to implement a whitening process based on the clutter model and demonstrate that it leads to improved tumor detection; and 4) to explore the feasibility of using microwave backscatter to classify the shape an object. The proposed shape classification study may lead to future work on tumor classification for enhancing the specificity of microwave imaging as a breast cancer screening tool.